In recent years, the field of autonomous driving has garnered increasing interest. Beyond ensuring the reliable operation of autonomous vehicles (AV), increasing attention has been directed towards understanding how these vehicles make decisions and predictions. Enhancing user trust in AVs requires developing situational awareness and decision-making processes that approximate human-level performance. Incorporating these capabilities in AV not only improves safety but also facilitates more intuitive and reliable human-machine interactions. Achieving this requires AI models capable of interpreting and responding to complex road scenarios in a manner similar to an experienced human driver. The ability to accurately predict and respond to dynamic traffic conditions is critical for the success and widespread adoption of AVs.